# FAmodel: Construct a Factor Model In tsfa: Time Series Factor Analysis

## Description

The default method constructs a FAmodel. Other methods extract a FAmodel from an object.

## Usage

 ```1 2 3 4 5 6``` ``` FAmodel(obj, ...) ## Default S3 method: FAmodel(obj, Omega=NULL, Phi=NULL, LB=NULL, LB.std=NULL, stats=NULL, ...) ## S3 method for class 'FAmodel' FAmodel(obj, ...) ```

## Arguments

 `obj` The loadings matrix (B) in the default (constructor) method. In other methods, an object from which the model should be extracted. `Omega` Covariance of the idiosyncratic term. `Phi` Covariance of the factors. `LB` Factor score predictor matrix. `LB.std` The standardized factor score predictor matrix. `stats` An optional list of statistics from model estimation. `...` arguments passed to other methods or stored in the object.

## Details

The default method is the constructor for `FAmodel` objects. Other methods extract a `FAmodel` object from other objects that contain one. The loadings must be supplied to the default method. Omega, Phi, and LB are included when the object comes from an estimation method, but are not necessary when the object is being specified in order to simulate. The model is defined by

y(t) = B f(t) + eps(t),

where the factors f(t) have covariance Phi and eps(t) have covariance Omega. The loadings matrix B is M x k, where M is the number of indicator variables (the number of indicators in y) and k is the number of factors.

A FAmodel.

## Author(s)

Paul Gilbert

`TSFmodel`, `estFAmodel`

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10``` ``` B <- t(matrix(c(0.9, 0.1, 0.8, 0.2, 0.7, 0.3, 0.5, 0.5, 0.3, 0.7, 0.1, 0.9), 2,6)) z <- FAmodel(B) z loadings(z) ```

### Example output

```Loading required package: GPArotation

Attaching package: 'dse'

The following objects are masked from 'package:stats':

acf, simulate

[,1] [,2]
[1,]  0.9  0.1
[2,]  0.8  0.2
[3,]  0.7  0.3
[4,]  0.5  0.5
[5,]  0.3  0.7
[6,]  0.1  0.9

\$Omega
NULL

\$Phi
NULL

\$LB
NULL

\$LB.std
NULL

\$stats
NULL

attr(,"class")
[1] "FAmodel"
[,1] [,2]
[1,]  0.9  0.1
[2,]  0.8  0.2
[3,]  0.7  0.3
[4,]  0.5  0.5
[5,]  0.3  0.7
[6,]  0.1  0.9
```

tsfa documentation built on May 29, 2017, 6 p.m.